NNCH {adehabitat}R Documentation

Nearest Neighbor Convex Hulls (LoCoH)

Description

NNCH computes the home range of several animals using the LoCoH family of methods.

Usage

NNCH(xy, id = NULL, k = c(10), unin = c("m", "km"),
     unout = c("m2", "ha", "km2"), status = FALSE,
     duplicates = 1, hog.limit = 500, r = NULL, a = NULL,
     min.k = NULL, max.k = NULL)

Arguments

xy a data frame containing the coordinates of the relocations of the monitored animals
id a factor giving the identity of the animal for each relocation
k if defined, the Fixed k LoCoH algorithm (k-NNCH) is used; the number of nearest neighbors minus one out of which to create convex hulls
r if defined, the Fixed r LoCoH algorithm is used; the convex hulls are created out of all points within r distance from the root points
a if defined, the Adaptive LoCoH algorithm is used; create convex hulls from the maximum number of nearest neighbors such that the sum of their distances is less than or equal to a
unin the units of the relocations coordinates. Either "m" for meters or "km" for kilometers
unout the units of the output areas. Either "m2" for square meters, "km2" for square kilometers or "ha" for hectares
status if TRUE print out occasional progress messages as we analyze the data
duplicates a setting to determine how duplicated points are handled. If a number, duplicated points, are displaces duplicates amount in a random direction, if "delete" all but one copy of duplicated points are deleted, if "ignore" no special handling of duplicated points (could create zero area hulls)
hog.limit if less than the number of points, a slow but memory efficient algorithm is used
min.k for use with Fixed r LoCoH and Adaptive LoCoH a "floor" for the value of k (ie. if the value of k found using the algorithm is less than min.k, set k equal to min.k)
max.k for use with Fixed r LoCoH and Adaptive LoCoH a "ceiling" for the value of k (ie. if the value of k found using the algorithm is more than max.k, set k equal to max.k)

Value

NNCH returns a list of class NNCH.

Warning

These functions require the package gpclib.

Note

The LoCoH family of methods for locating Utilization Distributions consists of three algorithms: Fixed k LoCoH, Fixed r LoCoH, and Adaptive LoCoH. All the algorithms work by constructing a small convex hull for each point, and then incrementally merging the hulls together from smallest to largest into isopleths. The 10% isopleth contains 10% of the points and represents a higher utilization the the 100% isopleth that contains all the points.

Fixed k LoCoH: Also known as k-NNCH, Fixed k LoCoH is described in Getz and Willmers (2004). The convex hull for each point is constructed from the (k-1) nearest neighbors to that point. Hulls are merged together from smallest to largest based on the area of the hull.
Fixed r LoCoH: In this case, hulls are created from all points within r distance of the root point. When merging hulls, the hulls are primarily sorted by the value of k generated for each hull (the number of points contained in the hull), and secondly by the area of the hull.
Adaptive LoCoH: Here, hulls are created out of the maximum nearest neighbors such that the sum of the distances from the nearest neighbors is less than or equal to d. Use the same hull sorting as Fixed r LoCoH.
Fixed r LoCoH and Adaptive LoCoH are discussed in a forthcoming paper (Getz et al).
All of these algorithms can take a signifigant amount of time. Time taken increases exponentially with the size of the data set.

Author(s)

Scott Fortmann-Roe scottfr@gmail.com
Clement Calenge clement.calenge@oncfs.gouv.fr

References

Getz, W.M. & Wilmers, C.C. (2004). A local nearest-neighbor convex-hull construction of home ranges and utilization distributions. Ecography, in press.
Getz, W.M., Fortmann-Roe, S.B, Lyons, A., Ryan, S., Cross, P. (in preparation). LoCoH methods for the construction of home ranges and utilization distributions. in preparation.

See Also

NNCH.select for plotting, rasterization, conversion to shapefiles, and management of the objects of class NNCH. NNCH.area for functions computing the homerange area.

Examples

## Not run: 
data(chamois)
xy <- chamois$locs

(nn <- NNCH(xy, k=c(6,7)))
summary(nn)
NNCH.select(nn, k=7)

## Graphical exploration
plot(nn, k=7)

## rasterization:
asc <- ascgen(chamois$locs,nrcol=100)
asc <- NNCH.asciigrid(nn, k=7, asc=asc)  
image(asc)
## End(Not run)


[Package adehabitat version 1.8.3 Index]